Stefan Bleeck

Structural and functional asymmetry of lateral Heschl's gyrus reflects pitch perception preference

The relative pitch of harmonic complex sounds, such as instrumental sounds, may be perceived by decoding either the fundamental pitch (f0) or the spectral pitch (fSP) of the stimuli. We classified a large cohort of 420 subjects including symphony orchestra musicians to be either f0 or fSP listeners, depending on the dominant perceptual mode. In a subgroup of 87 subjects, MRI (magnetic resonance imaging) and magnetoencephalography studies demonstrated a strong neural basis for both types of pitch perception irrespective of musical aptitude. Compared with f0 listeners, fSP listeners possessed a pronounced rightward, rather than leftward, asymmetry of gray matter volume and P50m activity within the pitch-sensitive lateral Heschls gyrus. Our data link relative hemispheric lateralization with perceptual stimulus properties, whereas the absolute size of the Heschls gyrus depends on musical aptitude.

Structural, Functional, and Perceptual Differences in Heschl's Gyrus and Musical Instrument Preference

Abstract: The musical pitch of harmonic complex sounds, such as instrumental sounds, is perceived primarily by decoding either the fundamental pitch (keynote) or spectral aspects of the stimuli, for example, single harmonics. We divided 334 professional musicians, including symphony orchestra musicians, 75 amateur musicians, and 54 nonmusicians, into either fundamental pitch listeners or spectral pitch listeners. We observed a strong correlation between pitch perception preference and asymmetry of brain structure and function in the pitch‐sensitive lateral areas of Heschls gyrus (HG), irrespective of musical ability. In particular, fundamental pitch listeners exhibited both larger gray matter volume measured using magnetic resonance imaging (MRI) and enhanced P50m activity measured using magnetoencephalography (MEG) in the left lateral HG, which is sensitive to rapid temporal processing. Their chosen instruments were percussive or high‐pitched instruments that produce short, sharp, or impulsive tones (e.g., drums, guitar, piano, trumpet, or flute). By contrast, spectral pitch listeners exhibited a dominant right lateral HG, which is known to be sensitive to slower temporal and spectral processing. Their chosen instruments were lower‐pitched melodic instruments that produce rather sustained tones with characteristic changes in timbre (e.g., bassoon, saxophone, french horn, violoncello, or organ). Singers also belonged to the spectral pitch listeners. Furthermore, the absolute size of the neural HG substrate depended strongly on musical ability. Overall, it is likely that both magnitude and asymmetry of lateral HG, and the related perceptual mode, may have an impact on preference for particular musical instruments and on musical performance.

Uncovering auditory evoked potentials from cochlear implant users with independent component analysis

Auditory evoked potentials (AEPs) provide an objective measure of auditory cortical function, but AEPs from cochlear implant (CI) users are contaminated by an electrical artifact. Here, we investigated the effects of electrical artifact attenuation on AEP quality. The ability of independent component analysis (ICA) in attenuating the CI artifact while preserving the AEPs was evaluated. AEPs recovered from CI users were systematically correlated with age, demonstrating that individual differences were well preserved. CI users with high-quality AEPs were characterized by a significantly shorter duration of deafness. Finally, a simulation study revealed very high spatial correlations between original and recovered normal hearing AEPs (r>.95) that were previously contaminated with CI artifacts. The results confirm that after ICA, good quality AEPs can be recovered, facilitating the objective, noninvasive study of auditory cortex function in CI users.

Semi-automatic attenuation of cochlear implant artifacts for the evaluation of late auditory evoked potentials.

Electrical artifacts caused by the cochlear implant (CI) contaminate electroencephalographic (EEG) recordings from implanted individuals and corrupt auditory evoked potentials (AEPs). Independent component analysis (ICA) is efficient in attenuating the electrical CI artifact and AEPs can be successfully reconstructed. However the manual selection of CI artifact related independent components (ICs) obtained with ICA is unsatisfactory, since it contains expert-choices and is time consuming. We developed a new procedure to evaluate temporal and topographical properties of ICs and semi-automatically select those components representing electrical CI artifact. The CI Artifact Correction (CIAC) algorithm was tested on EEG data from two different studies. The first consists of published datasets from 18 CI users listening to environmental sounds. Compared to the manual IC selection performed by an expert the sensitivity of CIAC was 91.7% and the specificity 92.3%. After CIAC-based attenuation of CI artifacts, a high correlation between age and N1-P2 peak-to-peak amplitude was observed in the AEPs, replicating previously reported findings and further confirming the algorithms validity. In the second study AEPs in response to pure tone and white noise stimuli from 12 CI users that had also participated in the other study were evaluated. CI artifacts were attenuated based on the IC selection performed semi-automatically by CIAC and manually by one expert. Again, a correlation between N1 amplitude and age was found. Moreover, a high test-retest reliability for AEP N1 amplitudes and latencies suggested that CIAC-based attenuation reliably preserves plausible individual response characteristics. We conclude that CIAC enables the objective and efficient attenuation of the CI artifact in EEG recordings, as it provided a reasonable reconstruction of individual AEPs. The systematic pattern of individual differences in N1 amplitudes and latencies observed with different stimuli at different sessions, strongly suggests that CIAC can overcome the electrical artifact problem. Thus CIAC facilitates the use of cortical AEPs as an objective measurement of auditory rehabilitation.

Contralateral inhibitory and excitatory frequency response maps in the mammalian cochlear nucleus

There is increasing evidence that the responses of single units in the mammalian cochlear nucleus can be altered by the presentation of contralateral stimuli, although the functional significance of this binaural responsiveness is unknown. To further our understanding of this phenomenon we recorded single‐unit (n = 110) response maps from the cochlear nucleus (ventral and dorsal divisions) of the anaesthetized guinea pig in response to presentation of ipsilateral and contralateral pure tones. Many neurones showed no evidence of input from the contralateral ear (n = 41) but other neurones from both ventral and dorsal cochlear nucleus showed clear evidence of contralateral inhibitory input (n = 61). Inhibitory response patterns were divided into two groups. In 36 neurones, contralateral tone‐evoked inhibition was closely aligned with the ipsilateral excitatory response map (± 0.33 octaves) often extending to low stimulus levels. In 25 neurones, higher threshold contralateral inhibitory responses were found, mostly centred at frequencies greater than 0.33 octaves below the ipsilateral excitation. A few neurones (n = 8) exhibited responses consistent with excitatory input from the contralateral ear, which was closely aligned with the ipsilateral excitation, and were found exclusively in the dorsal cochlear nucleus. The latency of the contralateral interaction was, on average, longer than the ipsilateral latency. Interaural level difference curves are similar to other reports from the cochlear nucleus. Our results are consistent with the idea that contralateral interactions arise from a variety of direct and indirect neuronal projections.

The time course of recovery from suppression and facilitation from single units in the mammalian cochlear nucleus.

The responses to two identical, consecutive pure tone stimuli with varying inter-stimulus intervals (delta ts) were measured for 89 neurons in the cochlear nucleus of the anaesthetised guinea pig. We observed two main effects; either a decrease (suppression) or an increase (facilitation) in response to the second tone followed by an exponential recovery. Response behaviour correlated with the unit type; primary-like, primary-like with notch and transient-chopper units showed a recovery from suppression that was very similar to that already reported in the auditory nerve. For chopper units the strength of the adaptation was correlated with the units regularity of spike discharge; sustained chopper (CS) units showed less suppression than transient choppers. Onset units showed complete suppression at short delta ts. Pause/Build (PB) units responded with increased activity to the second tone. In contrast to previous studies in the cochlear nucleus the recovery from suppression or facilitation was well described by a single exponential function, enabling us to define a recovery time constant and a maximum suppression/facilitation. There appeared to be a hierarchy in the time constant of recovery with PB and CS units showing the longest recovery times and onset units showing the shortest.

Using genetic algorithms to find the most effective stimulus for sensory neurons

Genetic algorithms (GAs) can be used to find maxima in large search spaces in a relatively short period of time. We have used GAs in electrophysiological experiments to find the most effective stimulus (MES) for sensory neurons in the cochlear nucleus and inferior colliculus of anaesthetised guinea pigs. The MES is the stimulus that elicits the greatest number of spikes from a unit. We show that GAs provide an effective means of determining the best combination of up to four parameters for sinusoids with amplitude modulation. Using GAs, we have found tuning to modulation frequencies as a function of carrier frequency, sound level and temporal asymmetry. These results demonstrate the suitability of GAs in electrophysical experiments for estimating the position of the most effective stimulus in a specified parameter space.

Speech enhancement based on neural networks improves speech intelligibility in noise for cochlear implant users

&NA; Speech understanding in noisy environments is still one of the major challenges for cochlear implant (CI) users in everyday life. We evaluated a speech enhancement algorithm based on neural networks (NNSE) for improving speech intelligibility in noise for CI users. The algorithm decomposes the noisy speech signal into time‐frequency units, extracts a set of auditory‐inspired features and feeds them to the neural network to produce an estimation of which frequency channels contain more perceptually important information (higher signal‐to‐noise ratio, SNR). This estimate is used to attenuate noise‐dominated and retain speech‐dominated CI channels for electrical stimulation, as in traditional n‐of‐m CI coding strategies. The proposed algorithm was evaluated by measuring the speech‐in‐noise performance of 14 CI users using three types of background noise. Two NNSE algorithms were compared: a speaker‐dependent algorithm, that was trained on the target speaker used for testing, and a speaker‐independent algorithm, that was trained on different speakers. Significant improvements in the intelligibility of speech in stationary and fluctuating noises were found relative to the unprocessed condition for the speaker‐dependent algorithm in all noise types and for the speaker‐independent algorithm in 2 out of 3 noise types. The NNSE algorithms used noise‐specific neural networks that generalized to novel segments of the same noise type and worked over a range of SNRs. The proposed algorithm has the potential to improve the intelligibility of speech in noise for CI users while meeting the requirements of low computational complexity and processing delay for application in CI devices. HighlightsAn algorithm for improving speech understanding in noise for cochlear implant users is evaluated.Significant improvements were found for stationary and non‐stationary noise types.It generalizes to a novel speaker and works over a range of signal‐to‐noise ratios.The small algorithmic delay makes it suitable for real‐time application.

Enhancement of forward suppression begins in the ventral cochlear nucleus

A neuron׳s response to a sound can be suppressed by the presentation of a preceding sound. It has been suggested that this suppression is a direct correlate of the psychophysical phenomenon of forward masking, however, forward suppression, as measured in the responses of the auditory nerve, was insufficient to account for behavioural performance. In contrast the neural suppression seen in the inferior colliculus and auditory cortex was much closer to psychophysical performance. In anaesthetised guinea-pigs, using a physiological two-interval forced-choice threshold tracking algorithm to estimate suppressed (masked) thresholds, we examine whether the enhancement of suppression can occur at an earlier stage of the auditory pathway, the ventral cochlear nucleus (VCN). We also compare these responses with the responses from the central nucleus of the inferior colliculus (ICc) using the same preparation. In both nuclei, onset-type neurons showed the greatest amounts of suppression (16.9–33.5 dB) and, in the VCN, these recovered with the fastest time constants (14.1–19.9 ms). Neurons with sustained discharge demonstrated reduced masking (8.9–12.1 dB) and recovery time constants of 27.2–55.6 ms. In the VCN the decrease in growth of suppression with increasing suppressor level was largest for chopper units and smallest for onset-type units. The threshold elevations recorded for most unit types are insufficient to account for the magnitude of forward masking as measured behaviourally, however, onset responders, in both the cochlear nucleus and inferior colliculus demonstrate a wide dynamic range of suppression, similar to that observed in human psychophysics.

Relationship between speech recognition in noise and sparseness

Abstract Objective: Established methods for predicting speech recognition in noise require knowledge of clean speech signals, placing limitations on their application. The study evaluates an alternative approach based on characteristics of noisy speech, specifically its sparseness as represented by the statistic kurtosis. Design: Experiments 1 and 2 involved acoustic analysis of vowel-consonant-vowel (VCV) syllables in babble noise, comparing kurtosis, glimpsing areas, and extended speech intelligibility index (ESII) of noisy speech signals with one another and with pre-existing speech recognition scores. Experiment 3 manipulated kurtosis of VCV syllables and investigated effects on speech recognition scores in normal-hearing listeners. Study sample: Pre-existing speech recognition data for Experiments 1 and 2; seven normal-hearing participants for Experiment 3. Results: Experiments 1 and 2 demonstrated that kurtosis calculated in the time-domain from noisy speech is highly correlated (r > 0.98) with established prediction models: glimpsing and ESII. All three measures predicted speech recognition scores well. The final experiment showed a clear monotonic relationship between speech recognition scores and kurtosis. Conclusions: Speech recognition performance in noise is closely related to the sparseness (kurtosis) of the noisy speech signal, at least for the types of speech and noise used here and for listeners with normal hearing.